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This chapter examines the affordances of social media to understand how groups are experienced through social media. Specifically, the chapter presents a theoretical model to understand how affordances of social media promote or suppress entitativity.

Participants (N=265) were recruited through snowball sampling to answer questions about their recent Facebook status updates. Confirmatory factor analysis (CFA) was used to examine the goodness of fit for our model.

We validate a model of entitativity as it occurs through the affordances offered by social media. Participant’s knowledge that status update responders were an interacting group outside of Facebook affected their perceptions of interactivity in the responses. Interactivity and history of interactions were the strongest predictors of status update entitativity. Further, status update entitativity had positive relationships with overall Facebook entitativity as well as group identity.

To encourage group identity through social media, managers need to increase employees’ perceptions of entitativity, primarily by enabling employees to see the interactions of others and to contribute content in social media platforms.

This is the only study we know of that empirically examines how groups are experienced through social media. Additionally, we draw from an affordance perspective, which helps to generalize our findings beyond the site of our study.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.